Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories

Lu, Yingcheng; Li, Xiang; Tian, Qingjiu; Zheng, Guang; Sun, Shaojie; Liu, Yongchao; Yang, Qiang

doi:10.1080/01490419.2013.793633

Cited by 54 publications

(22 citation statements)

References 24 publications

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“…In contrast, estimating oil slick thickness has been notoriously difficult, and even today there is still controversy on whether measuring or estimating oil thickness is feasible [ Fingas and Brown , ; Svejkovsky et al ., ]. To date, nearly all algorithms developed to estimate oil slick thickness from optical remote sensing have employed spectra measured in a laboratory or well‐controlled environments [ Wettle et al ., ; Svejkovsky et al ., ; Lu et al ., ]. This difficulty arises from knowledge that the reflectance spectra of oil and seawater can be significantly different in a natural environmental setting than those measured in the lab due to different observing conditions.…”

Section: Discussionmentioning

confidence: 99%

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Refinement of the critical angle calculation for the contrast reversal of oil slicks under sunglint

Sun

Zhang

et al. 2016

JGR Oceans

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It has long been observed that oil slicks under sunglint can reverse their optical contrast against nearby oil‐free seawater. Such a phenomenon has been described through both empirical statistical analysis of the sunglint strength and modeled theoretically using a critical angle concept. The critical angle, in this model, is the angle at which the image pixels show no or negligible contrast between oiled and nonoiled seawater. Pixels away from this critical angle show either positive or negative contrast from the oil‐free pixels. Although this concept has been fully demonstrated in the published literature, its calculation needs to be further refined to take into account: (1) the different refractive indices of oil slicks (from natural seeps) and seawater and (2) atmospheric effects in the sensor‐measured radiance. Using measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) over oil films in the Gulf of Mexico, we show improvement in the modeled and MODIS‐derived reflectance over oil slicks originated from natural seeps after incorporating these two factors in the model. Specifically, agreement between modeled and measured sunglint reflectance is found for both negative and positive‐contrasting oil slicks. These results indicate that surface roughness and reflectance from oil films can be estimated given any solar/viewing geometry and surface wind. Further, this model might be used to correct the sunglint effect on thick oil under similar illumination conditions. Once proven possible, it may allow existing laboratory‐based models, which estimate oil thickness after such corrections, to be applied to remote sensing imagery.

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Section: Discussionmentioning

confidence: 99%

“…[], and Lu et al . []). Perhaps the most popular technique involves using Synthetic Aperture Radar (SAR) sensor data [ Hodgins et al ., ; Zheng et al ., ; Keramitsoglou et al ., ; Garcia‐Pineda et al ., ].…”

Section: Introductionmentioning

confidence: 99%

Refinement of the critical angle calculation for the contrast reversal of oil slicks under sunglint

Sun

Zhang

et al. 2016

JGR Oceans

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“…[], and Lu et al . []), including optical sensors [ Chust and Sagarminaga , ; Giammona et al ., ; Hu et al ., ; Lu et al ., ; Sugioka et al ., ; Sun and Hu , ; Sun et al ., ], synthetic aperture radar (SAR) [ Brekke and Solberg , ; Garcia‐Pineda et al ., ; Hodgins et al ., ; Keramitsoglou et al ., ; Zheng et al ., ], thermal sensors [ Asanuma et al ., ; Cai et al ., ; Cross , ; Innman et al ., ; Leifer et al ., ; Lu et al ., ; Salisbury et al ., ; Tseng and Chiu , ], and laser fluorescence [ Brown et al ., ; Brown and Fingas , ]. These different technologies possess unique characteristics, theoretical bases, related data processing techniques, and quantitative remote sensing models.…”

Section: Introductionmentioning

confidence: 99%

“…Marine oil slicks result primarily from oil spill accidents [Hu et al, 2003;Leifer et al, 2012;Lu et al, 2013a;Wang and Shen, 2010;Zhong and You, 2011] and natural hydrocarbon seeps [Howari, 2004;Hu et al, 2009;MacDonald et al, 1993MacDonald et al, , 2002O'Brien et al, 2005]. It is estimated that 47% of such slicks arise from naturally occurring seeps [Kvenvolden and Cooper, 2003].…”

Section: Introductionmentioning

confidence: 99%

Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle

Zhou

Liu

et al. 2017

JGR Oceans

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The critical angle at which the brightness of oil slicks and oil‐free seawater is reversed occurs under sunglint and is often shown as an area of uncertainty due to different roughness and surface Fresnel reflection parameters. Consequently, differentiating oil slicks from the seawater in these areas using optical sensors is a challenge. Polarized optical remote sensing techniques provide complementary information for intensity imagery with different physical properties and, thus, possess the ability to resolve this difficult problem. In the polarized reflectance model, the degree of linear polarization (DOLP) of sunglint depends on accurately knowing the Stokes parameter for the reflected light, and varies with the refractive index of the surface layer and viewing angles. For the polarized detection of oil slicks, the highest sensitivity of the DOLP to the refractive index is located within the specular reflection direction where the sum of the solar and sensor zenith angles is 82.6°. The modeled results clearly indicate that the DOLP of oil slicks is weaker in comparison with oil‐free seawater under sunglint. Using measurements from the space‐borne Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) over the Deepwater Horizon oil spill in the Gulf of Mexico, we illustrate that the PARASOL‐derived DOLP difference between the oil spill and seawater is obvious and is in accordance with the modeled results. These preliminary results suggest that the potential of multiangle measurement and feasibility of deriving refractive index of ocean surface from space‐borne sensors need further researches.

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“…Wang and Shen [21,22] developed a three-dimensional integrated model that provides great flexibility for modeling oil spill accidents in complex geometries such as tidal creeks, barriers, and islands. Currently, an unstructured grid is primarily used to simulate the solid boundary for the study of oil spills in complex terrains [6,[21][22][23][24][25][26][27][28]. Alves et al [1] proposed a three-step model to predict and assess shoreline and offshore susceptibility to oil spills for confined basins with islands, which comprises the leading edge in the study of oil spills in complex terrains.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling of Marine Oil Spills in the Luanjiakou District, near the Port of Yantai

Tang

et al. 2018

Discrete Dynamics in Nature and Society

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This paper presents a simulation method for oil spills in a multi-island area. The simulation considers three parts, which consist of (1) the spreading of an oil slick on its edge as well as the diffusion and drift under dynamic actions, (2) the evaporation and spreading thickness of an oil slick in its interior, and (3) the adsorption and emulsification near shorelines and islands. The Euler-Lagrange method is adopted to track the spill location and particles positions on the edge of oil slicks. A mathematical model of marine oil spills is established for the Luanjiakou District of the Port of Yantai. The flow field verification shows that the BIAS of tidal level, flow velocity, and flow direction is below ±10 cm, 0.11 m/s, and ±2 ∘ , respectively, and the oil spill verification captures satisfactory results. Hence, the proposed model could reproduce the oil spill process in this region. Then, we simulate oil spills under various operating conditions. It is concluded that the transport of oil slicks is mainly influenced by flood/ebb currents, whereas the wind plays a major role in the drift and thickness of oil slicks. The study provides an important reference to controlling and handling of accidental oil spills.

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Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories

Cited by 54 publications

References 24 publications

Refinement of the critical angle calculation for the contrast reversal of oil slicks under sunglint

Refinement of the critical angle calculation for the contrast reversal of oil slicks under sunglint

Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle

Mathematical Modeling of Marine Oil Spills in the Luanjiakou District, near the Port of Yantai

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